Work

Machine learning for hemodynamic instability prediction and hemorrhage management in trauma and perioperative care

Year: 2026

Type: article

Source: Current Opinion in Anaesthesiology

DOI: 10.1097/aco.0000000000001624

Authors: Joshua Le, Walter Rusin, Alexandre Joosten, Maxime Cannesson, Ravi Pal

Institutions: University of Vermont, University of California, Los Angeles

Language: English

Topic: Machine Learning in Healthcare

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering

Awards: Machine Learning of Physiological Waveforms and Electronic Health Record Data to Predict, Diagnose, and Treat Hemodynamic Instability in Surgical Patients, Biomedical Informatics Tools for Applied Perioperative Physiology, Personalized Risk Prediction for Prevention and Early Detection of Postoperative Failure to Rescue

OpenAlex ID: W7128816764

FWCI:

Cites: 34

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